The positive relationship between relative conidial culturability (after exposure to UVA) and concentration of melanin was indicated also by linear regression for both sunny and shady microniches.
Experimental results indicate that by linear regression and parameter mapping, the estimation model precision was very high.
Correlations of different parameters were analyzed by linear regression and indicated by the square of the corresponding regression coefficient (R).
This observation was confirmed by linear regression analysis, indicating that the involvement of stroma in macrodissected gene expression profiles was minor.
UV-visible spectrophotometric assay was determined by linear regression and the r value indicated the measure of goodness-of-fit for linear regression.
Habituation was indicated by a negative, whereas dishabituation was marked by a positive slope as calculated by linear regression (y = ax + b, where a is the slope of habituation and b the intercept of linear regression) [9].
Habituation was indicated by a negative, whereas loss of habituation was marked by a positive slope as calculated by linear regression (y = ax + b, where a is the slope of habituation and b the intercept of linear regression) [28].
Linearity of the standard curves and correlation coefficients were obtained by linear regression analyzes.
The intercept and slope parameters were estimated by linear regression and the seasonal cycle by harmonic regression.
Various combinations of these proteins were used to predict radiation dose by linear regression.
